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Fog-Based Transcoding for Crowdsourced Video Livecast

机译:基于雾的转码用于众包视频直播

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Recent years have witnessed the booming popularity of CLS platforms, through which numerous amateur broadcasters live stream their video contents to viewers around the world. The heterogeneous qualities and formats of the source streams, however, require massive computational resources to transcode them into multiple industrial standard quality versions to serve viewers with distinct configurations, and the delays to the viewers of different locations should be well synchronized to support community interactions. This article attempts to address these challenges and to explore the opportunities with new generation computation paradigms, in particular, fog computing. We present a novel fog-based transcoding framework for CLS platforms to offload the transcoding workload to the network edge (i.e., the massive number of viewers). We evaluate our design through our PlanetLab-based experiment and real-world viewer transcoding experiment.
机译:近年来,目睹了CLS平台的蓬勃发展,众多业余广播公司通过它们向世界各地的观众直播其视频内容。但是,源流的质量和格式异质,需要大量的计算资源才能将其转码为多个行业标准质量版本,以为具有不同配置的观众提供服务,并且应很好地同步到不同位置的观众的延迟,以支持社区互动。本文试图解决这些挑战,并探索新一代计算范例(尤其是雾计算)带来的机遇。我们为CLS平台提供了一种基于雾的新颖代码转换框架,可将代码转换工作量转移到网络边缘(即大量观看者)。我们通过基于PlanetLab的实验和真实世界的观看者转码实验来评估我们的设计。

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